import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
import numpy as np

from plotly.offline import init_notebook_mode
init_notebook_mode()

df = pd.read_csv('../data/capture_fisheries.csv', skiprows=4)
df = df.dropna(how='all')

df['Country Name'] = df['Country Name'].str.replace('"', '')
years = [str(year) for year in range(1960, 2025)]
id_vars = ["Country Name", "Country Code", "Indicator Name", "Indicator Code"]

df_melted = df.melt(id_vars=id_vars, value_vars=years, 
                   var_name="Year", value_name="Production")
df_melted['Year'] = pd.to_numeric(df_melted['Year'])
df_melted['Production'] = pd.to_numeric(df_melted['Production'], errors='coerce')
df_melted = df_melted.dropna(subset=['Production'])

q95 = df_melted['Production'].quantile(0.95)
focused_data = df_melted[df_melted['Production'] <= q95]
zmax = focused_data['Production'].max()
zmin = focused_data['Production'].min()

enhanced_scale = [
    [0.0, '#E1F5FE'], 
    [0.1, '#B3E5FC'],  
    [0.2, '#81D4FA'], 
    [0.3, '#4FC3F7'], 
    [0.4, '#29B6F6'], 
    [0.5, '#039BE5'], 
    [0.6, '#0288D1'], 
    [0.7, '#0277BD'], 
    [0.8, '#01579B'],  
    [0.9, '#0D47A1'],  
    [1.0, '#1d1c47']  
]


total_production = df_melted.groupby(['Country Name', 'Country Code'])['Production'].sum().reset_index()

fig_total = px.choropleth(total_production,
                        locations="Country Code",
                        color="Production",
                        hover_name="Country Name",
                        color_continuous_scale=enhanced_scale,
                        range_color=[zmin, zmax],
                        labels={'Production': 'Production (metric tons)'},
                        projection="natural earth")

fig_total.update_layout(
    width=700,
    height=500,
    geo=dict(
        landcolor='#f0f0f0',
        lakecolor='#d0e0f0',
        bgcolor='white',
        showframe=True,
        framecolor='black'
    ),
    coloraxis_colorbar=dict(
        title="Production",
        thickness=20,
        len=0.75,
        tickvals=np.linspace(zmin, zmax, 6),
        ticktext=[f"{int(x):,}" for x in np.linspace(zmin, zmax, 6)]
    ),
    margin={'t': 9, 'r': 20, 'b': 33, 'l': 18},
    title={
        'text': '<b>Total Fisheries Production per Country</b>',
        'x': 0.42,
        'xanchor': 'center', 
        'y': 0.95,
        'yanchor': 'top',
        'font': {
            'color': '#0a2463',
        }
    }
)

fig_total.add_annotation(x=0.02, y=0.02,
                   xref="paper", yref="paper",
                   showarrow=False,
                   align='left',
                   xanchor='left', yanchor='bottom',
                   text="Total fisheries production per country since 1960.<br>" + \
                        'Hover over countries to see their specific production and drag to see different areas.<br>')

fig_total.update_annotations(
    font=dict(color='#0a2463')
)

fig_total.show()